What's Next – BFS/DFS & Components

• Next lecture introduces graph traversal algorithms that systematically visit all vertices reachable from a starting point. Breadth-First Search (BFS) explores layer by layer, while Depth-First Search (DFS) explores as deeply as possible before backtracking.
• BFS finds the shortest path in unweighted graphs by exploring vertices in order of increasing distance from the source. It uses a queue data structure and is perfect for level-order traversal, finding connected components, and minimum hop distance calculations.
• DFS is ideal for detecting cycles, topological sorting of directed acyclic graphs (DAGs), and finding strongly connected components. It uses a stack (or recursion) and explores each branch completely before moving to the next.
• Both algorithms operate directly on the graph representations you learned today—adjacency lists and matrices. Understanding these data structures is essential preparation since traversal efficiency depends heavily on how you've encoded your graph. Keep your representation functions handy for the next lecture!